Revisiting the design issues of local models for Japanese predicate-argument structure analysis

Research output: Contribution to journalArticlepeer-review

Abstract

The research trend in Japanese predicateargument structure (PAS) analysis is shifting from pointwise prediction models with local features to global models designed to search for globally optimal solutions. However, the existing global models tend to employ only relatively simple local features; therefore, the overall performance gains are rather limited. The importance of designing a local model is demonstrated in this study by showing that the performance of a sophisticated local model can be considerably improved with recent feature embedding methods and a feature combination learning based on a neural network, outperforming the state-of-theart global models in F1on a common benchmark dataset.

Original languageEnglish
JournalUnknown Journal
Publication statusPublished - 2017 Oct 12

ASJC Scopus subject areas

  • General

Fingerprint Dive into the research topics of 'Revisiting the design issues of local models for Japanese predicate-argument structure analysis'. Together they form a unique fingerprint.

Cite this